The allegations of the Barclays case-rampant front-running of large institutional orders by high-frequency traders, done with the complicity of the dark pool operator-constitute perhaps the biggest nightmare that institutional buyside traders face in using dark pools. Little wonder they flock to dark pools run by the most reputable Wall Street banks, like Barclays, which had promised them that those pools would be safe.
An Introduction to Dark Pools
All eyes are on the June numbers, due out in early this month, which may show the impact the Barclays case could have on dark pool activity. As with the HFT frenzy, the past several weeks have seen dark pools become the subject of announced regulatory proposals, revealing data dumps and shocking enforcement actions.
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Underpinning this all, however, is a question of whether dark pools-secretive and murky by their very nature-still add value to the markets, or are now simply a venue that allows abuse to go on when the lights go out. The first volley in this most recent battle was fired on June 2, when the Financial Industry Regulatory Authority FINRA released trading activity data from alternative trading systems ATSs , including the roughly 40 operating dark pools.
It was the first time that the investing public and many financial professionals had a look at those numbers, which previously had been provided only to traders and had been based on voluntary reporting from some, but not all, dark pools on an aggregated, monthly basis. The market already knew that total ATS volume had reached about 40 percent of all stock trades, compared to just 15 percent in , according to TABB.
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That knowledge, coupled with the FINRA data, seemed to make many market pros look at dark pools with renewed urgency. What does that do to quotes in the marketplace? In a widely watched speech before bankers, exchange executives and traders just three days after the FINRA data release, White offered pointed criticism of high-speed trading and dark pools, citing both as examples of technology-driven change that may not always have the most positive impact on the market.
Addressing dark pools, White said transparency is a hallmark of U. Nagy agreed, saying he also understood why White was addressing both HFT and dark pools in the same harsh tones. While Nagy said he is cautious about how tentatively regulators are approaching the issue-he noted that a set of SEC dark pool rule proposals crafted in were never acted upon and have been gathering dust ever since-he is encouraged even by the incremental movement.
Downey, chief executive of OneChicago, a registered securities futures exchange, began his career on the floor of the American Stock Exchange ASE in the mids. However, when only a few people give out information, those who release proprietary information, intentions, and strategies are at a disadvantage.
Having accurate prices is necessary for resource allocation and efficiency. Critics believe the negative impact of dark pools on price discovery will prompt participants to start their own independent research.
This research, in turn, causes superfluous time and monetary expenditures. As the number of dark pools grows, each has its own rules. While this competition allows for more personalization and may be beneficial, there also is more unnecessary information and liquidity fragmentation. Traders and regulators are concerned about problems arising from the fragmentation: more difficulty in searches and exclusivity of information.
Traders cannot make decisions as easily because of a loss of price discovery. They sometimes compensate for this loss by seeking more information. However, the search becomes more challenging due to the fragmentation of information and liquidity. Not only must traders seek out information on prices, they must also learn the rules of various pools. They must search more places to find the liquidity to obtain the most desirable sale. However, as discussed, this search can incur significant time and money costs. Most basically, and uncontroversially, it involves bodily injury.
If, for example, a schoolteacher strikes a child, we would say Second, fragmentation occurs because information is more prized. Rather than being readily available to everyone, participants compete to gain exclusive access. For example, people compete for indications of interest IOIs. These revelations are internal, and participants remain anonymous to the public. When this order is executed, the venue sends IOIs to a select group for approximately half a second, a significant amount of time in modern electronic markets, before it sends it to others to try to keep the order on their market.
For the most part, public exchanges are not exclusive. In contrast, we have discussed how dark pools sometimes limit access to institutional investors, MTFs, clients, exchanges, broker dealers, and ATSs. While this in and of itself is not necessarily unfair, critics claim that potential participants are unfairly denied access to pools. These concerns are significant because traders will need to access dark pools more in their search for liquidity as pools grow and public exchanges shrink.
Exclusion can be particularly detrimental to those who are blocked from large dark pools that have a lot of liquidity. In an arena like dark pools where information is not readily available and where having it can mean making or losing money, information becomes highly priced. However, some observers are not confident that this happens. This concern is rooted in an inherent problem dark pools face: keeping proprietary information safe even though revealing some is necessary in order to match orders. Consequently, regulators, such as the SEC, and others worry that an exclusive group receives more, better, or earlier information.
Dark Pool Trading System
Private information is leaked to several actors: gamers, the dark pool itself, their prop desks, and undisclosed liquidity partners. We divide these actors into the types of information they receive: indirect and direct. For gamers, information leakage is not direct.
If the response is favorable, allowing them to determine there is a big buy order, gamers will accumulate shares in small blocks and then sell them en masse when the price is highest for a profit. This in turn creates an unfair playing field, where some have greater access to information than others.
Resolving this problem—for example, by removing some clients from their pools, or having minimum quantities of orders—is not necessarily in the interest of dark pools. Higher share volumes determine success. Critics hint that dark pools frequently ignore situations of information leakage. The other three actors, the dark pool itself, their prop desks, and undisclosed liquidity partners, receive direct information.
The dark pool operator receives information directly, as it sometimes participates in its own pool even though operators are expected to be third parties who protect information. Prop desks exist within firms who operate dark pools, such as investment banks.
Dark Pools: Fifty Shades of Trade
Public exchanges do not have such entities. Many argue this gives all three groups an unfair advantage.
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Participants must give dark pools their information and do so with the expectation that it will not be used against them. Detractors emphasize that clients are not able to respond properly before it is too late. Some worry about increased no execution risks in dark pools. Trades depend on matching and matching orders may be harder in an anonymous environment. People do not know supply and demand making adjustments to an equilibrium point more difficult. Thus, those who are on the side with more orders may not be able to get their orders filled.
Good may be used to refer to anything — it is a general term that expresses positive value about something or assigns positive value to something. Nevertheless, in philosophy the term takes on special meaning and that meaning is particularly related to ethics. Studies on dark pools give mixed answers. Another study by the CFA Institute arrives at a different conclusion.
It suggests that so long as dark pools remain less than fifty percent of total trading, they improve market quality. However, when a majority of trading takes place in dark pools then market quality decreases. Overall, studies may use different pools, be performed at different times, measure different traits, and have different procedures for evaluating their measurements, among other potential differences.
Thus, studies frequently arrive at conflicting answers. Since they are so hard to compare, it is not easy to determine which are best to use when evaluating dark pools. The fact that studies often conflict is not particularly encouraging. If we do not know exactly what is good and what is bad about dark pools, how can we analyze their ethical implications?
We do so by analyzing dark pools through two frameworks: consequentialism and deontology. These theories are important for two reasons. First, they are significant in that together, they cover both the ends and the principles of a process, which allows us to focus on the general picture. This view is important as the details of dark pools are often unknown. Second, the two frameworks represent the contrasting focus of supporters and detractors, who prefer consequentialism and deontology respectively.
We have the opportunity to measure the strength of arguments of each side. Consequentialism, as its name indicates, holds that only the consequences of an act matter. Good consequences mean that an act or choice is morally right, while bad consequences mean the opposite. In this case, we consider only the economic and financial outcomes of dark pools because people primarily trade to earn profits. Whether their methods are the best, or meet any other standard, is not relevant in this analysis.
If participation in a dark pool costs traders money, then dark pools are not ethical. However, if dark pools generate more profits or savings for traders, then dark pools are ethical. As we have seen, studies arrive at different conclusions on a variety of dark pool issues due to different measuring techniques and the anonymity associated with these platforms.